<abstract> <p>Major emergencies cause massive financial risk and economic loss. In the context of major emergencies, we propose the GPD-CAViaR model to depict the extreme risks of financial sectors, and utilize the TVP-SV-VAR model to analyze their transmission effect. We find that (ⅰ) the securities sector has the highest extreme risks among the four financial sectors; (ⅱ) when major emergencies occur, the extreme risks of various financial sectors increase rapidly; (ⅲ) the transmission effect in short term is stronger than that in medium and long term; and (ⅳ) the transmission effects at different time points are relatively consistent.</p> </abstract>

Several public events have drawn renewed attention to the connectedness of the international stock market since the financial crisis of 2008. We investigate systemic and regional connectedness among stock markets around the world at major public events by constructing correlation networks for 46 markets based on the dynamic time-warping method. We find that (i) geographic regionalization is typically observed in the stock market network, in which France is dominant, (ii) Europe has the greatest and the Middle East and Africa the least within-region connectedness, (iii) the correlation network structure is highly integrated and compact at major public events, and global events influence the international stock market more significantly than regional events do, and (iv) the importance of China reaches its peak during the era of Sino-US trade friction, showing that public events have enormous impacts on the countries involved.